Market pressures in the Oil & Gas industry are challenging traditional business models. Evolving market conditions, a growing lack of a skilled workforce, and the need to address sustainability are just a few of the areas causing disruptions in the industry. Oil & Gas companies must respond to calls to maximize production and revenue, reduce risk and operational costs, and find new, more efficient ways of working. Successful companies are integrating technology, such as digital twins, to respond to these growing pressures.

Digital twins – digital representations or virtual replicas of physical assets – allow enterprises to capture relevant information about any asset, analyze and develop actionable insights from volumes of data, and quickly learn everything they need to know to improve their operation. Yet the benefits of digital twins extend beyond operations; when used across the enterprise, Oil & Gas companies can change traditional work models and build a foundation for future profitability and growth.

Benefits of Digital Twins

Managing equipment and processes efficiently, especially in an asset- and operations-intensive industry such as Oil & Gas, is critical. Recent advancements in connectivity, artificial intelligence/machine learning (AI/ML), IoT devices, and sensors make managing industrial equipment and complex processes more intuitive and feasible. And combining these technologies with digital twin functionality allows Oil & Gas enterprises to realize an immediate impact on their business.

But technology is rarely a “one size fits all” strategy. Wipro has worked with Oil & Gas owners, and operators to incorporate Industry 4.0 solutions like digital twin technology. The results demonstrate that the industry can benefit from digital twins in three common areas: data integration and asset monitoring, modelling and planning, and predictive analytics and data visualization These, in turn, ultimately help companies maximize efficiencies, scale growth, accelerate operational performance, and can support an enterprise’s efforts to reduce their carbon footprint.

Data Integration and Asset Monitoring

Digital twins enable the integration of operational, maintenance, and engineering data to improve the efficiency of hard-to-reach assets. This un-siloed structure allows digital twins to access, process and monitor data in real time for faster improvements in production efficiency. Real-time data generated by each component in the plant can be leveraged with the Digital Passport (a single “golden record” of repository data of the physical asset) to gain insight into asset health, monitor operational parameters, and identify and fix anomalies or malfunctions. For example, Wipro created a digital twin strategy for a large crude oil producer in North America that supported multiple business units. The digital twin solution helped to reduce production downtime and improved asset efficiency, leading to higher throughput.

Modelling and Planning

In combination with AI models and predictive analytics, Digital Twins promote better planning by simulating “what-if” scenarios, including workforce flow and resource needs. Models can use past data and/or real-time data to simulate future production planning, thereby enabling smarter KPI and goal management. In addition, digital twins can advance health and safety protocols, improve workforce training, and facilitate turnaround planning. In one instance, Wipro worked with a global Oil & Gas company to develop field simulations that supported strategic planning to revise drilling processes and resource coverage. The use of digital twins also helped the company achieve its plan of advanced health and safety behaviors and more effective onboarding for new workers.

Predictive Analytics and Data Visualization

A highly beneficial use of digital twins is the ability to visualize and predict maintenance issues before they happen. Predictive models can be used to create maintenance schedules that can significantly reduce unplanned downtime. With 3D visualizations and dashboards, engineering and process teams can gain valuable insights from real-time data and collaborate to solve problems, even on remote sites and oil rigs that can be difficult and risky to access. For example, Wipro worked with a large European Oil & Gas company to create a digital twin ecosystem that predicted potential equipment shutdowns. Since the physical asset was in a remote location, visualizations helped the company reduce travel expenses, and predictive analytics suggested the optimal staff hours needed to perform in-person assessments.

Four Steps to Maximize the Potential of Digital Twins

The use of digital twins is a way companies can leverage the fundamentals of Industry 4.0 to enable success through innovation, intelligence, and integration. Successful companies start by creating a digital twin roadmap that is modular by design. A flexible design enables companies to include more data, like supplier variables, and allows future scaling to strengthen the core business. Planning for what-if scenarios is vital for asset-intensive industries like Oil & Gas. But digital twins also provide fact-based decision support for scenario models like production imbalances, changes in global economic and political conditions, equipment reliability, and can even help a company on its sustainability journey.  

Oil & Gas companies can use digital twins to improve data traceability, remove data silos and improve operations by focusing on high-value solutions first. By thinking beyond operations, Oil & Gas companies can derive insights that enable the enterprise to be more proactive and productive across the entire business. Even investment strategies can be improved, as the virtual environment provides an ideal testing ground for “what-if” scenarios before applying them to a real-world situation.

The four steps below can help Oil & Gas companies maximize the potential of digital twins across the enterprise:

• Build support within the organization, securing a commitment from leadership and end users
  
• Define a clear set of expectations, timetable, and metrics for success, and realize that outcomes are different by use case
• Develop a limited number of applications in areas that will provide the most value for brown field and green field assets – solving for high-value problems first
• Remain flexible; allow for modifications to the digital twin as real-world conditions change

A Good Time for Digital Twins

The adoption of Industry 4.0 and digital twins has increased in recent years. According to Altair, three out of four organizations now utilize digital twins in some capacity, with 85% citing success in achieving sustainability goals and 50% using them for real-time monitoring. For enterprises that have yet to adopt digital twins, new technology is making digital twins a reliable strategy to improve operations and save money. And enterprises that are currently using digital twins can maximize the benefits of their investment by adding 5G connectivity, IoT, AI/ML, and additive manufacturing. Among these new capabilities, Altair found that real-time analytics and AI are in the top four used with digital twins to analyze massive data sets for transformative insights that improve targeted outcomes. Digital twins are no longer just an interesting idea. They are highly transformative to many asset-intensive industries like Oil & Gas.

Ganesh Kumar Bukka

Global Head, Industry 4.0, Wipro Engineering

Ganesh has more than 25 years of diversified experience across strategy, business transformation, engineering, R&D, sustainability, manufacturing engineering, and operational efficiency. He has worked with global enterprises – manufacturing, automotive, retail, energy and utilities, healthcare and life sciences, and telecommunications – to improve their operating efficiency, increase revenue, and remain competitive.